Protein Structure Prediction and Analysis

About the course  |  Intended audience  |  Prerequisites  |  Content details  |  Scheduled events

About the course

Determining the three-dimensional (3D) structure of a protein from its amino acid sequence is essential for understanding its biological function. Experimental methods remain the standard for obtaining high-resolution structures, but they can be costly, time-consuming, and technically challenging for certain proteins.

This course provides a practical introduction to computational approaches for predicting protein structures from amino acid sequences. The course focuses on AlphaFold, a method that has transformed protein structure prediction through its near-experimental prediction accuracy.

Participants will learn how to retrieve structural information from public databases, evaluate the quality of predicted models, and visualise protein structures using ChimeraX. The course also covers multimer predictions, prediction of ligand binding sites, and molecular docking approaches.

By the end of the course, participants should be able to generate protein structure predictions and critically assess the quality and limitations of the computational methods used.

Teaching is primarily hands-on, with short presentations and demonstrations introducing the concepts and methods needed to predict, analyse, and visualise protein structures.

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Intended audience

This course is suitable for:

• researchers and students interested in protein structure analysis
• participants who want practical experience with computational protein structure prediction methods
• researchers seeking to use predicted protein structures to investigate biological function
• participants interested in visualisation and interpretation of protein structural data

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Prerequisites

Participants should have:

• an understanding of the basics of protein structure

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Content details

The course covers the following topics:

• Introduction to protein structure prediction
  Introduces the principles of computational protein structure prediction and discusses the role of predictive methods alongside experimental approaches.
• Structure prediction with AlphaFold
  Covers the use of AlphaFold for predicting protein structures from amino acid sequences and introduces the concepts underlying its prediction framework.
• Retrieving structural information from public databases
  Introduces public repositories of protein structural information and demonstrates how to access and use existing structural data.
• Evaluating predicted protein structures
  Covers approaches for assessing the quality and reliability of predicted protein models and discusses the interpretation and limitations of prediction confidence metrics.
• Protein structure visualisation with ChimeraX
  Introduces methods for visualising and exploring protein structures using ChimeraX and demonstrates approaches for communicating structural features effectively.
• Multimer structure prediction
  Covers the prediction of protein complexes and introduces methods for modelling interactions between multiple protein chains.
• Prediction of ligand binding sites
  Introduces computational approaches for identifying potential ligand binding regions and interpreting their biological relevance.
• Molecular docking
  Covers the principles of molecular docking and demonstrates how predicted protein structures can be used to investigate protein-ligand interactions.

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